Solar radio pulsating structures during September 9, 2001 at meter wavelength

Pulsating structures recorded at 237 MHz that are associated to decimetric continuum enhancement during the September 9, 2001 solar radio burst are described. We analyzed the radiopolarimetric data recorded at the Trieste Solar Radio System (INAF—Trieste Astronomical Observatory—Basovizza Observing Station) with very high time resolution (1 ms) at metric frequencies. Two different types of pulsations that occur in about 4 minutes at the same frequency are described. The possible mechanisms are analyzed and some parameters of the associated magnetic structure are estimated.     

Magnetic and velocity field variations in the active regions NOAA 10486 and NOAA 10488

We study the magnetic and velocity field evolution in the two magnetically complex active regions NOAA 10486 and NOAA 10488 observed during October–November 2003. We have used the available data to examine net flux and Doppler velocity time profiles to identify changes associated with evolutionary and transient phenomena. In particular, we report detection of rapid moving features observed in NOAA 10486 during the maximum phase of the X17.2/4B superflare of October 28, 2003. The velocity of this moving feature is estimated around 40 km/s, i.e., much greater than the usual Hα flare-ribbons’ separation speed of 3–10 km/s, but similar to the velocity of seismic waves, i.e., ～ 45 km/s reported earlier by Kosovichev & Zharkova (1998).     

Hα intensity oscillations in large flares

We reinvestigate the problem of Hα intensity oscillations in large flares, particularly those classified as X-class flares. We have used high spatial and temporal resolution digital observations obtained from Udaipur Solar Observatory during the period 1998–2006 and selected several events. Normalized Lomb-Scargle periodogram method for spectral analysis was used to study the oscillatory power in quiet and active chromospheric locations, including the flare ribbons.     

Do mixing models with different input requirement yield similar streamflow source contributions? Case study: A tropical montane catchment

Hydrogeochemical based mixing models have been successfully used to investigate the composition and source identification of streamflow. The applicability of these models is limited due to the high costs associated with data collection and the hydrogeochemical analysis of water samples. Fortunately, a variety of mixing models exist, requiting different amount of data as input, and in data scarce regions it is likely that preference will be given to models with the lowest requirement of input data. An unanswered question is if models with high or low input requirement are equally accurate. To this end, the performance of two mixing models with different input requirement, the mixing model analysis (MMA) and the end-member mixing analysis (EMMA), were verified on a tropical montane headwater catchment (21.7 km²) in the Ecuadorian Andes. Nineteen hydrogeochemical tracers were measured on water samples collected weekly during 3 years in streamflow and eight potential water sources or end-members (precipitation, lake water, soil water from different horizons and springs). Results based on 6 conservative tracers, revealed that EMMA (using all tracers) and MMA (using pair-combinations out of the 6 conservative ones), identified the same end-members: rainfall, soil water and spring water., as well as, similar contribution fractions to streamflow from rainfall 21.9% and 21.4%, soil water 52.7% and 52.3%, and spring water 26.1% and 28.7%, respectively. Our findings show that a hydrogeochemical mixing model requiring a few tracers can provide similar outcomes than models demanding more tracers as input data. This underlines the value of a preliminary detailed hydrogeochemical characterization as basis to derive the most cost-efficient monitoring strategy.     

Quantifying groundwater sensitivity and resilience over peninsular India

Groundwater in India plays an important role to support livelihoods and maintain ecosystems and the present rate of depletion of groundwater resources poses a serious threat to water security. Yet, the sensitivity of the hydrological processes governing groundwater recharge to climate variability remains unclear in the region. Here we assess the groundwater sensitivity (precipitation–recharge relationship) and its potential resilience towards climatic variability over peninsular India using a conceptual water balance model and a convex model, respectively in 54 catchments over peninsular India. Based on the model performance using a comprehensive approach (Nash Sutcliffe Efficiency [NSE], bias and variability), 24 out of 54 catchments are selected for assessment of groundwater sensitivity and its resilience. Further, a systematic approach is used to understand the changes in resilience on a temporal scale based upon the convex model and principle of critical slowing down theory. The results of the study indicate that the catchments with higher mean groundwater sensitivity (GWS) encompass high variability in GWS over the period (1988–2011), thus indicating the associated vulnerability towards hydroclimatic disturbances. Moreover, it was found that the catchments pertaining to a lower magnitude of mean resilience index incorporates a high variability in resilience index over the period (1993–2007), clearly illustrating the inherent vulnerability of these catchments. The resilience of groundwater towards climatic variability and hydroclimatic disturbances that is revealed by groundwater sensitivity is essential to understand the future impacts of changing climate on groundwater and can further facilitate effective adaptation strategies.     

A comparative analysis of pansharpening techniques on QuickBird and WorldView-3 images

Nowadays, different image pansharpening methods are available, which combine the strengths of different satellite images that have different spectral and spatial resolutions. These different image fusion methods, however, add spectral and spatial distortions to the resultant images depending on the required context. Therefore, a careful selection of the fusion method is required. Simultaneously, it is also essential that the fusion technique should be efficient to cope with the large data. In this paper, we investigated how different pansharpening algorithms perform, when applied to very high-resolution WorldView-3 and QuickBird satellite images effectively and efficiently. We compared these 27 pansharpening techniques in terms of quantitative analysis, visual inspection and computational complexity, which has not previously been formally tested. In addition, 12 different image quality metrics available in literature are used for quantitative analysis purpose.     

Impacts of climate change on building energy demands in the intra-Americas region

It was recently reported a regional warming in the intra-Americas region where sea surface temperature exhibited increases exceeding 0.15 °C/decade and an accelerated air temperature rise that could impact building energy demands per capita (EDC). Reanalysis data is used herein to quantify the impacts of these warming trends on EDC. Results of the analysis depict a Southern Greater Antilles and inland South America with a positive annual EDC rate of 1–5 kWh per year. The Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP) 2.6 and 4.5 scenarios were selected to analyze energy demand changes in the twenty-first century. A multi-model ensemble forecasts an EDC increase of 9.6 and 23 kWh/month in the RCP2.6 and RCP4.5 at the end of the twenty-first century, which may increase average building cooling loads in the region by 7.57 GW (RCP2.6) and 8.15 GW (RCP4.5), respectively. Furthermore, 4 of 9 (RCP2.6) and 7 of 9 (RCP4.5) of the major countries in this region have EDCs ranging between 1887 and 2252 kWh/year at the end of this century. Therefore, increased energy production and improved energy infrastructure will be required to maintain ideal indoor building conditions at the end of the twenty-first century in these tropical coastal regions as consequence of a warmer climate.     

Climate-smart agriculture: perspectives and framings

This paper offers a systematic analysis of the concepts and contexts that frame the climate-smart agriculture (CSA) discourse in the academic and policy literature. Documents (n?=?113) related to CSA and published in peer-reviewed journals, books, working papers, and scientific reports from 2004 to 2016 were reviewed. Three key trends emerged from the analysis: studies are biased towards global policy agendas; research focuses on scientific and technical issues; and the integration of mitigation, adaptation, and food security (the three pillars of CSA) is becoming a popular scholarly solution. Findings suggest that CSA is a fairly new concept used to describe a range of adaptation and mitigation practices without a specific set of criteria. Although CSA is often framed around the three pillars, the underlying issues constructing the discourse differ at global, developing, and developed country scales. Although there is increasing research on developing countries, particularly in relation to how CSA can transform smallholder agriculture, there is a paucity of research documenting the experiences from developed countries. The findings suggest that research on CSA needs to move beyond solely focussing on scientific approaches and only in certain geographical contexts. If CSA is to be applicable for farmers across the globe, then cross-disciplinary research that is underpinned by broad socio-economic and political contexts is essential to understand how differences in narratives might affect implementation on-the-ground in both developing and developed countries.

POLICY RELEVANCE

Although policy makers are increasingly supportive of the climate-smart agriculture (CSA) approach, the rhetoric has largely been developed on the basis of scientific and technical arguments. The political implications of varying perspectives have resulted in a growing divide between how developing and developed countries frame solutions to the impacts of climate change on agriculture under the 2015 Paris Agreement. Different framings are part of the explanation for why the scope of CSA is being rethought, with the scientific community redirecting attention to seeking a separate work programme under the United Nations Framework Convention on Climate Change (UNFCCC). The current policy framing of CSA will give no new policy direction unless it grounds itself in the smallholder farmer and civil society contexts.     

Fijian villagers adapt to changes in local fisheries

This paper analyzes some of the problems encountered by a village-run fishing cooperative in rural Fiji. Concern about the limited success of this fishing cooperative led the villagers of Kaba Point, Fiji to ask for biological and socioeconomic studies to determine the roots of the cooperative’s problems. The villagers also required an assessment of their proposal to revitalize the cooperative through a development scheme that would enable them to increase their catch. The surveys, undertaken by researchers from the University of the South Pacific and the Fiji Fisheries Division, indicate that the area has been overfished, primarily through the widespread local and commercial use of gillnets and the reliance on fishing as a sole source of village income, and further expansion of the current resource exploitation patterns would be very damaging. In addition, although the cooperative provides an important sense of communalism in the village, only a few people regularly provide fish to the coop. The semi-subsistence lifestyle of rural Fiji is one factor limiting villagers participation in full-time fishing activities. The traditional social and management structures inherent in this village (especially, marine tenure, chiefly responsibility for the community, and a demonstrated history of communal projects) can form a strong basis for a modern community-based marine management program. However, if not carefully watched, resources can also be locally mismanaged because of the increasing demands of the modern market-driven economy.     

Prediction of weather parameters on a very short time scale by an Auto Regressive process for aviation flight planning

Forecasting weather parameters such as temperature and pressure with a reasonable degree of accuracy three hours ahead of the scheduled departure of an aircraft helps economic and efficient planning of aircraft operations. However, these two parameters exhibit a high degree of persistency and have nonstationary mean and variance at sub-periods (i.e. at 0000, 0300, 0600,…, 2100UTC). Hence these series have been standardised (to have mean 0 and variance 1) and thereafter seasonal differenced (lag 8) to achieve almost near stationarity. An attempt has been made to fit the standardised and seasonal differenced series of Chennai (a coastal station) and Trichy (an inland station) airport into an Auto Regressive (AR) process. The model coefficients have been estimated based on adaptive filter algorithm which uses the method of convergence by the steepest descent. The models were tested with an independent data set and diagnostic checks were made on the residual error series. An independent estimation of fractal dimension has also been made in this study to conform the number parameters used in the AR processes. The models contemplated in this study are parsimonious and can be used to forecast surface temperature and pressure.